In establishing communications networks it is often difficult to manage the demands on the network made by various stations, particularly when the individual stations may have different usage and operational parameters. For example, a wireless network may be established e.g., by a wireless Internet service provider (WISP), that services multiple independent stations, e.g., customer provided equipment (CPE). Individual stations may make demand the bandwidth of the network to which the station connects at different times and intensities. Further, individual stations may be capable of operating at different rates because of structural limitations (e.g., hardware, software, firmware of the station) or because of geographic limitations (e.g., strength of connection to the network access point(s)).
Although in general, the demands on networks, from devices including mobile devices, such as smart phones and tablets, have increased with increasing prevalence in recent years, networks are becoming increasing stressed. Further, the availability of multimedia streaming (e.g., video, sound, data) over these same networks has become more common. Given the fast advance in mobile computing power and far-reaching wireless Internet access, more and more users view streamed videos on their mobile devices. The detection of network congestion has become increasingly important for network operators attempting to maximize user experience on the network. Even as network operators are ever increasing the capacity of their networks, the demand for bandwidth is growing at an even faster pace. Managing network growth and dealing with congestion in the infrastructure is particularly important because of the high cost of licensed radio spectrum and limitations of radio access network (RAN) equipment utilized by wireless mobile networks.
Network elements may be able to provide operators a view into the current state of traffic in their network, but they do not provide overall diagnostic health indicators in a manner that could readily allow a network operator to identify and potentially address potential (or actual) problems with the network, including any elasticity and capability in the network, as well as rapidly and intuitively indicating how various stations are influencing the network by at the current time and historically. Such indicators of network health would be important for improving and enhancing a network's ability to deliver data in a reliable and sustainable fashion. For example, a minimum data rate may be required to prevent stalling and re-buffering during the streaming of multimedia content to stations in a network; ensuring sufficient bandwidth to all (or a majority of) stations/users is important to quality of experience. Typically, multimedia content providers are sufficiently equipped to deliver multimedia content at levels far beyond the capabilities of wireless infrastructure. Hence, the burden falls on wireless service providers to implement network data optimization to ease the traffic burden and maximize the experience of each and every user on the network. Currently, only limited tools are available, which may not provide sufficient information (and in an easily digestible form) to properly monitor a network.
For example, one tool useful for understanding the health of a network is the constellation diagram. A constellation diagram is generally a representation of a signal modulated by a digital modulation scheme such as quadrature amplitude modulation or phase-shift keying. It displays the signal as a two-dimensional scatter diagram in the complex plane at symbol sampling instants. In a more abstract sense, it represents the possible symbols that may be selected by a given modulation scheme as points in the complex plane. Measured constellation diagrams can be used to recognize the type of interference and distortion in a signal. Constellation diagrams may be generated by measuring the error vector magnitude (EVM) of a signal, which indicates the deviation of the signal from the ideal.
Unfortunately, in practice, even with increasingly fast processors associated with wireless devices (including access points), generation of an action constellation diagram, e.g., using actual measured EVM information, is time consuming, and may require the addition of monitoring components which is impractical and expensive. In particular, the real-time or near-real time display of EVM information (or even reasonably approximate EVM information) would be greatly beneficial.
Further, although many wireless networks operating through an access point are capable of switching channels, current channel-selection/switching techniques are not optimal, and, if they automatically switch channels at all, select the new channel based on the immediate needs, without optimizing at all, or without optimizing based on the likely ongoing needs of the network. Tools such as those described above may be used to optimize an access point and thus a network (or more than one network) communicating or through the access point. For example, it would be beneficial to optimize the choice of the frequency channel (and/or the channel bandwidth) for a network. In particular, it would be beneficial to optimize a frequency channel for a network based on both the operation and/or needs of all or a subset of client devices (e.g., the biggest users, highest priority users, etc.) as well as the actual and/or historical state of the frequency spectrum surrounding the client (and AP) devices. It would also be beneficial to automatically select an optimal channel and/or bandwidth.
Described herein are apparatuses, including devices and systems (e.g., tools) and methods, for monitoring, interpreting, and improving the overall health of a network that may address some or all of the problems addressed above.